Sorry but you have no idea what you're talking about. Minsky, together with Seymour Pappert, wrote a book where they pointed out very real practical and theoret

Sorry but you have no idea what you're talking about. Minsky, together with Seymour Pappert, wrote a book where they pointed out very real practical and theoretical limitations of single-layer perceptrons, which at the time (and for many years before) were the only neural networks that anyone had ever successfully managed to train. You see, Minsky and Pappert's book, titled "Perceptrons", was published in 1969. Note well that this was a whole fifteen years before Rumelehart proposed backpropagation as an efficient algorithm for training neural nets, in 1986. Indeed, without backpropagation, even if multi-layer perceptrons were theoretically capable of learning functions like XOR and parity (the two examples of the limitations of single-layer perceptrons in the Minsky and Pappert book) nobody knew how to train multi-layer perceptrons in practice until Rumelhart. That's the whole point of backpropagation, and that's why every single graduate and undergraduate course in neural nets teaches backpropagation: because without it, you're stuck with single-layer perceptrons. Minsky and Pappert weren't the ones who "slowed down AI" as per your comment, it was neural net researchers who failed to get their shit together and figure out how to train their systems efficiently, who couldn't progress beyond their weaker, lesser single-layer perceptrons, and who accused Minsky and Pappert of foul play in order to cover their own research's inadequacies. Minsky and Pappert did a big favour to all those early perceptron researchers, by rubbing their nose in their mess, and forcing them to recongise the limitations of their systems. If it wasn't for Minsky and Pappert, it would have probably taken another couple of decades before neural net researchers got off their arses and improved their work. And, btw: Minsky himself was a staunch connectionist and build neural network systems. So quit spreading the ahistorical nonsense that he was somehow the big bad of early neural net research. Early neural net research was a shambles, is the truth; even more so than it is today.